web02.fireside.fm Wed, 20 May 2026 18:13:54 -0500 Fireside (https://fireside.fm) The It's Innate! Podcast - Episodes Tagged with “Number Cognition” https://itsinnate.fireside.fm/tags/number%20cognition Wed, 20 May 2026 11:00:00 -0400 Two opinionated developmental cognitive scientists wax theoretical about how infants and children acquire knowledge! en-us episodic A podcast by two developmental cognitive scientists Deon Benton & Jenny Wang Two opinionated developmental cognitive scientists wax theoretical about how infants and children acquire knowledge! no Deon Benton & Jenny Wang theitsinnatepodcast@gmail.com Episode 39: Give-N you Bayes and Backpropagation (Pt. II) https://itsinnate.fireside.fm/39 932fb469-3f12-4fd9-b07b-47445af3d6ac Wed, 20 May 2026 11:00:00 -0400 Deon Benton & Jenny Wang full Deon Benton & Jenny Wang 2:03:56 no <p>We're back with Part II. We continue our discussion of how to apply Bayesian models to number cognition, but in this segment we talk about another Lee and Sarnecka (2011) paper in which they show how the very same Bayesian model can be used to test two different theories of how children acquire number. We also talk about the strengths and weakness of large and small artificial neural networks, and Deon makes the case for why small models shouldn't be abandoned. We then talk a bit about what a model of the give-N task might look like and what role realism plays in the model.</p> <p>Links</p> <p>Lee, M. D., &amp; Sarnecka, B. W. (2011). Number-knower levels in young children: Insights from Bayesian modeling. Cognition, 120(3), 391-402.<a href="https://www.sciencedirect.com/science/article/pii/S0010027710002283?casa_token=CIRzaM6HEdwAAAAA:k8kWVn9Y6td5T-JEwnPTcPt64Pgiw1rqtLV58BCvomCo51GP_36UAc6Wpy3kevkZvN1xiqvY" target="_blank" rel="nofollow noopener">Link</a> </p> number cognition, mechanism, computational modeling, connectionism, bayesian inference We're back with Part II. We continue our discussion of how to apply Bayesian models to number cognition, but in this segment we talk about another Lee and Sarnecka (2011) paper in which they show how the very same Bayesian model can be used to test two different theories of how children acquire number. We also talk about the strengths and weakness of large and small artificial neural networks, and Deon makes the case for why small models shouldn't be abandoned. We then talk a bit about what a model of the give-N task might look like and what role realism plays in the model.

Links

Lee, M. D., & Sarnecka, B. W. (2011). Number-knower levels in young children: Insights from Bayesian modeling. Cognition, 120(3), 391-402.Link

]]> We're back with Part II. We continue our discussion of how to apply Bayesian models to number cognition, but in this segment we talk about another Lee and Sarnecka (2011) paper in which they show how the very same Bayesian model can be used to test two different theories of how children acquire number. We also talk about the strengths and weakness of large and small artificial neural networks, and Deon makes the case for why small models shouldn't be abandoned. We then talk a bit about what a model of the give-N task might look like and what role realism plays in the model.

Links

Lee, M. D., & Sarnecka, B. W. (2011). Number-knower levels in young children: Insights from Bayesian modeling. Cognition, 120(3), 391-402.Link

]]>